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Daniel Mansilla, Jesper Tveit, Harald Aurlien, Tamir Avigdor, Victoria Ros-Castello, Alyssa Ho, Chifaou Abdallah, Jean Gotman, Sándor Beniczky, Birgit Frauscher
Abstract
The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource-limited settings and reduce the workload at specialized centers. However, to facilitate broad clinical implementation, it is essential to establish generalizability across diverse patient populations and equipment. We assessed whether SCORE-AI demonstrates diagnostic accuracy comparable to that of experts when applied to a geographically different patient population, recorded with distinct EEG equipment and technical settings.
